论文标题
一对早期和晚期的星系群集样品:一种新的研究光环组装偏置的方法,该偏置受约束模拟的辅助
A Pair of Early- and Late-Forming Galaxy Cluster Samples: a Novel Way of Studying Halo Assembly Bias Assisted by a Constrained Simulation
论文作者
论文摘要
光环组装偏置是一种指代黑物质光晕质量以外的大规模偏置的依赖性的现象,是标准宇宙学模型的基本特性。事实证明,在2005年首次发现,很难在观察上发现它,到目前为止只有少数令人信服的检测主张。主要障碍在于找到光环形成时间的准确代理。 In this study, by utilizing a constrained simulation that can faithfully reproduce the observed structures larger than $2\,$Mpc in the local universe, for a sample of 634 massive clusters at $z\le 0.12$, we find their counterpart halos in the simulation and use the mass growth history of the matched halos to estimate the formation time of the observed clusters.这使我们能够构建一对早期和晚期形成的簇,其质量与通过弱重力镜头测量,并且在$ \3σ$水平上有不同的质量,暗示了组装偏见的标志,这进一步佐证了集群星系的特性,包括最明亮的集群星系,并构成了Spatatial和Spatatial和Spatatial and Spatatial and Spatatial和数字。我们的研究铺平了一种基于纯粹基于观察到的数量的群集样品进一步检测组装偏差的方法。
The halo assembly bias, a phenomenon referring to dependencies of the large-scale bias of a dark matter halo other than its mass, is a fundamental property of the standard cosmological model. First discovered in 2005 from the Millennium Run simulation, it has been proven very difficult to be detected observationally, with only a few convincing claims of detection so far. The main obstacle lies in finding an accurate proxy of the halo formation time. In this study, by utilizing a constrained simulation that can faithfully reproduce the observed structures larger than $2\,$Mpc in the local universe, for a sample of 634 massive clusters at $z\le 0.12$, we find their counterpart halos in the simulation and use the mass growth history of the matched halos to estimate the formation time of the observed clusters. This allows us to construct a pair of early- and late-forming clusters, with similar mass as measured via weak gravitational lensing, and large-scale bias differing at $\approx 3σ$ level, suggestive of the signature of assembly bias, which is further corroborated by the properties of cluster galaxies, including the brightest cluster galaxy, and the spatial distribution and number of member galaxies. Our study paves a way to further detect assembly bias based on cluster samples constructed purely on observed quantities.